Electric arc characterisation and furnace process monitoring with optical emission spectroscopy and image analysis

Thesis event information

Date and time of the thesis defence

Place of the thesis defence

Linnanmaa, auditorium L5. Remote connection: https://oulu.zoom.us/j/66615277631

Topic of the dissertation

Electric arc characterisation and furnace process monitoring with optical emission spectroscopy and image analysis

Doctoral candidate

Master of Science Henri Pauna

Faculty and unit

University of Oulu Graduate School, Faculty of Technology, Process Metallurgy Research Unit

Subject of study

Process Metallurgy


Associate Professor Valentina Colla, Sant'Anna School of Advanced Studies


Professor Timo Fabritius, University of Oulu

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Light as the source of process information for more environmentally friendly steelmaking

New information on the recycled metal-based steelmaking in electric arc furnaces and ladle furnaces can be acquired by studying the light of the electric arc. In this doctoral dissertation, the light from the arc has been measured with optical emission spectroscopy (OES), which has the potential to work as a much needed real-time analysis method in process control. On the industrial scale, it has prospects to increase resource and energy efficiency.

Carbon dioxide emission reductions set for 2050 will most probably lead to a transition from an iron ore-based blast furnace process to electric steel production in electric arc furnaces and ladle furnaces. In these furnaces, recycled metal and sponge iron reduced by hydrogen are melted by a high-energy electrical discharge whose light contains a huge amount of information.

The main significance of the dissertation research is in the development of real-time process control with OES, which measures the light emitted by the arc and the melt surface. The arc forms a plasma in which compounds decompose into both charged and neutral atoms and molecules. The high energy of the plasma excites particles, causing them to emit light, or photons, at wavelengths characteristic to the particle. Atoms and molecules can be identified from the spectra based on the wavelengths of the photons, and e.g. plasma and melt surface temperature, plasma composition, and the effect of the atmosphere on the spectra can be evaluated from the data.

Characterisation of the pilot-scale furnace arc with OES and image analysis has helped to understand the behavior of the arc during the melting process, and the high impact of slag on arc properties is one of the main results of the study. In industrial OES spectra, on the other hand, the slag foaming and the time-evolution of the temperature of both the charge material and the melt temperatures can be monitored together with the evaluation of the slag composition. Industrial measurements have proven that OES is also suitable for studying industrial processes.
Last updated: 1.3.2023